Many biomedical, orthopaedic, and industrial applications are emerging that will benefit from
personalized neuromusculoskeletal models. Applications include refined diagnostics …

Over the past decades, the use of computational physics-based models representative of the
musculoskeletal (MSK) system has become increasingly popular in many fields of clinically …

Purpose To develop and validate a deep learning–based method for automatic quantitative
analysis of lower-extremity alignment. Materials and Methods In this retrospective study …

Neuromusculoskeletal models are a powerful tool to investigate the internal biomechanics of
an individual. However, commonly used neuromusculoskeletal models are generated via …

The generation of personalised and patient-specific musculoskeletal models is currently a
cumbersome and time-consuming task that normally requires several processing hours and …

Computational modelling is an invaluable tool for investigating features of human
locomotion and motor control which cannot be measured except through invasive …

Background Bone shapes strongly influence force and moment predictions of kinematic and
musculoskeletal models used in motion analysis. The precise determination of joint …

Accurate representation of subject-specific bone anatomy in lower-limb musculoskeletal
models is important for human movement analyses and simulations. Mathematical methods …

In biomechanical simulations, generic linearly scaled musculoskeletal anatomies are
commonly used to represent children, often neglecting or oversimplifying subject-specific …

Objective: The accuracy of a musculoskeletal model relies heavily on the implementation of
the underlying anatomical dataset. Linear scaling of a generic model, despite being time …